jev_scoreAssess inputs using 2-10 ordered rubric levels, returning a score, legend, and probabilities to support transparent, criteria-based evaluation.
Rate along ordered levels (2-10 concrete descriptions). Returns score + legend + probabilities.
| Name | Required | Description | Default |
|---|---|---|---|
| model | No | jev-latest | |
| state | Yes | ||
| criteria | Yes | ||
| endpoint | No | direct | |
| instructions | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must bear full behavioral disclosure. It mentions the output (score + legend + probabilities) but omits side effects, whether it calls a model, determinism, permissions, or rate limits. The schema hints at model and endpoint parameters, but the description does not clarify these behaviors.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded with the primary purpose, which is good. However, the parenthetical '(2-10 concrete descriptions)' is cryptic and could be misinterpreted. The structure is acceptable but not exemplary—it is concise but not optimally clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 5 parameters, 3 required, and no annotations, the description is under-specified. It fails to explain parameter semantics, usage context, and behavioral nuances beyond output. Even accounting for the output schema, the description does not equip an agent to call this tool correctly in varied situations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must explain parameter meaning. It hints that the tool uses '2-10 concrete descriptions' (likely for the criteria parameter) but does not explain 'state', 'instructions', 'model', or 'endpoint'. This leaves several parameters ambiguous.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb ('Rate') and a specific resource ('along ordered levels'), and mentions it returns score, legend, and probabilities. This distinguishes it from general evaluation tools, though it does not explicitly name sibling differentiators like jev_choice or jev_evaluate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives. No conditions, prerequisites, or situational context are provided, leaving the agent without explicit decision criteria for selecting this tool over its siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.